38 citations · 150 across the 20 of their papers we have counts for
20 papers
Local Diagnostics of Continuous Normalizing Flow for Out-of-Distribution Detection
Xinwei Cao, Mengxuan Lu, Torbjørn Svendsen +1
We address the problem of out-of-distribution (OOD) detection for target observations embedded in a subspace of the high dimensional data space. Using continuous normalizing flows…
Segmentation-free Goodness of Pronunciation
Xinwei Cao, Zijian Fan, Torbjørn Svendsen +1
Mispronunciation detection and diagnosis (MDD) is a significant part in modern computer-aided language learning (CALL) systems. Most systems implementing phoneme-level MDD through…
Non-native Children's Automatic Speech Assessment Challenge (NOCASA)
Yaroslav Getman, Tamás Grósz, Mikko Kurimo +1
This paper presents the "Non-native Children's Automatic Speech Assessment" (NOCASA) - a data competition part of the IEEE MLSP 2025 conference. NOCASA challenges participants to d…
Exploiting Foundation Models and Speech Enhancement for Parkinson's Disease Detection from Speech in Real-World Operative Conditions
Moreno La Quatra, Maria Francesca Turco, Torbjørn Svendsen +3
This work is concerned with devising a robust Parkinson's (PD) disease detector from speech in real-world operating conditions using (i) foundational models, and (ii) speech enhanc…
Developing Acoustic Models for Automatic Speech Recognition in Swedish
Giampiero Salvi
This paper is concerned with automatic continuous speech recognition using trainable systems. The aim of this work is to build acoustic models for spoken Swedish. This is done empl…
Dynamic Behaviour of Connectionist Speech Recognition with Strong Latency Constraints
Giampiero Salvi
This paper describes the use of connectionist techniques in phonetic speech recognition with strong latency constraints. The constraints are imposed by the task of deriving the lip…
Segment Boundary Detection via Class Entropy Measurements in Connectionist Phoneme Recognition
Giampiero Salvi
This article investigates the possibility to use the class entropy of the output of a connectionist phoneme recogniser to predict time boundaries between phonetic classes. The rati…
S-HR-VQVAE: Sequential Hierarchical Residual Learning Vector Quantized Variational Autoencoder for Video Prediction
Mohammad Adiban, Kalin Stefanov, Sabato Marco Siniscalchi +1
We address the video prediction task by putting forth a novel model that combines (i) a novel hierarchical residual learning vector quantized variational autoencoder (HR-VQVAE), an…
Hierarchical Residual Learning Based Vector Quantized Variational Autoencoder for Image Reconstruction and Generation
Mohammad Adiban, Kalin Stefanov, Sabato Marco Siniscalchi +1
We propose a multi-layer variational autoencoder method, we call HR-VQVAE, that learns hierarchical discrete representations of the data. By utilizing a novel objective function, e…
NAAQA: A Neural Architecture for Acoustic Question Answering
Jerome Abdelnour, Jean Rouat, Giampiero Salvi
The goal of the Acoustic Question Answering (AQA) task is to answer a free-form text question about the content of an acoustic scene. It was inspired by the Visual Question Answeri…
STEP-GAN: A Step-by-Step Training for Multi Generator GANs with application to Cyber Security in Power Systems
Mohammad Adiban, Arash Safari, Giampiero Salvi
In this study, we introduce a novel unsupervised countermeasure for smart grid power systems, based on generative adversarial networks (GANs). Given the pivotal role of smart grid…
From Visual to Acoustic Question Answering
Jerome Abdelnour, Giampiero Salvi, Jean Rouat
We introduce the new task of Acoustic Question Answering (AQA) to promote research in acoustic reasoning. The AQA task consists of analyzing an acoustic scene composed by a combina…
Beyond the Self: Using Grounded Affordances to Interpret and Describe Others' Actions
Giovanni Saponaro, Lorenzo Jamone, Alexandre Bernardino +1
We propose a developmental approach that allows a robot to interpret and describe the actions of human agents by reusing previous experience. The robot first learns the association…
CLEAR: A Dataset for Compositional Language and Elementary Acoustic Reasoning
Jerome Abdelnour, Giampiero Salvi, Jean Rouat
We introduce the task of acoustic question answering (AQA) in the area of acoustic reasoning. In this task an agent learns to answer questions on the basis of acoustic context. In…
Active Mini-Batch Sampling using Repulsive Point Processes
Cheng Zhang, Cengiz Öztireli, Stephan Mandt +1
The convergence speed of stochastic gradient descent (SGD) can be improved by actively selecting mini-batches. We explore sampling schemes where similar data points are less likely…
Language Bootstrapping: Learning Word Meanings From Perception-Action Association
Giampiero Salvi, Luis Montesano, Alexandre Bernardino +1
We address the problem of bootstrapping language acquisition for an artificial system similarly to what is observed in experiments with human infants. Our method works by associati…
Interactive Robot Learning of Gestures, Language and Affordances
Giovanni Saponaro, Lorenzo Jamone, Alexandre Bernardino +1
A growing field in robotics and Artificial Intelligence (AI) research is human-robot collaboration, whose target is to enable effective teamwork between humans and robots. However,…
Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition
Kalin Stefanov, Jonas Beskow, Giampiero Salvi
This paper presents a self-supervised method for visual detection of the active speaker in a multi-person spoken interaction scenario. Active speaker detection is a fundamental pre…
Semi-supervised Learning with Sparse Autoencoders in Phone Classification
Akash Kumar Dhaka, Giampiero Salvi
We propose the application of a semi-supervised learning method to improve the performance of acoustic modelling for automatic speech recognition based on deep neural net- works. A…
Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing
Akash Kumar Dhaka, Giampiero Salvi
We present a systematic analysis on the performance of a phonetic recogniser when the window of input features is not symmetric with respect to the current frame. The recogniser is…